// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2012 Desire Nuentsa Wakam <desire.nuentsa_wakam@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed

#define EIGEN_NO_DEBUG_SMALL_PRODUCT_BLOCKS
#include "sparse.h"
#include <Eigen/SPQRSupport>

template<typename MatrixType, typename DenseMat>
int
generate_sparse_rectangular_problem(MatrixType& A, DenseMat& dA, int maxRows = 300, int maxCols = 300)
{
	eigen_assert(maxRows >= maxCols);
	typedef typename MatrixType::Scalar Scalar;
	int rows = internal::random<int>(1, maxRows);
	int cols = internal::random<int>(1, rows);
	double density = (std::max)(8. / (rows * cols), 0.01);

	A.resize(rows, cols);
	dA.resize(rows, cols);
	initSparse<Scalar>(density, dA, A, ForceNonZeroDiag);
	A.makeCompressed();
	return rows;
}

template<typename Scalar>
void
test_spqr_scalar()
{
	typedef SparseMatrix<Scalar, ColMajor> MatrixType;
	MatrixType A;
	Matrix<Scalar, Dynamic, Dynamic> dA;
	typedef Matrix<Scalar, Dynamic, 1> DenseVector;
	DenseVector refX, x, b;
	SPQR<MatrixType> solver;
	generate_sparse_rectangular_problem(A, dA);

	Index m = A.rows();
	b = DenseVector::Random(m);
	solver.compute(A);
	if (solver.info() != Success) {
		std::cerr << "sparse QR factorization failed\n";
		exit(0);
		return;
	}
	x = solver.solve(b);
	if (solver.info() != Success) {
		std::cerr << "sparse QR factorization failed\n";
		exit(0);
		return;
	}
	// Compare with a dense solver
	refX = dA.colPivHouseholderQr().solve(b);
	VERIFY(x.isApprox(refX, test_precision<Scalar>()));
}
EIGEN_DECLARE_TEST(spqr_support)
{
	CALL_SUBTEST_1(test_spqr_scalar<double>());
	CALL_SUBTEST_2(test_spqr_scalar<std::complex<double>>());
}
